| | JUNE 20218CIOReviewIN MY OPINIONCaterpillar is synonymous with heavy machinery and, for more than 90 years, our products help our customers build a better world. We've also been driving industry-leading connectivity solutions for over 20 years, introducing our first telematics device in 1999. Nowadays, Caterpillar's growing digital team is supporting the company's digital strategy through advanced data science and IoT solutions.With onboard computers, sensors, and cameras, approximately one million assets are transmitting data to Caterpillar to enable advanced IoT analytics at scale. This data can include time-series data, machine health alerts, fuel usage, GPS, and operator-specific usage.Powered by data, Caterpillar's IoT analytics can provide customers value at a lower cost of ownership, increased productivity, safety, and reduced maintenance costs. We use analytics to tell when a machine or part of a machine needs to be serviced or replaced, how to operate more effectively to increase production, how to reduce operational costs, how to increase service life, and more.So, what is the future of this fast-growing field - IoT analytics?To answer this question, let us review and discuss the main trends and challenges in this field.Trend: The increasing amount of data. Challenge: Quality of available data. The Industrial Internet of Things (IIOT) is a data-generating engine for IoT analytics. For example, a large modern truck can have over 100 IoT sensors, each producing telematics data at 1 Hz frequency or faster. An analyst can face quality problems in working with such a large set of data. Missing batches or By Andrei Khurshudov, Ph.D., Director, IoT Analytics, CAT DigitalTHE BUILT ENVIRONMENT OF THE DATA CENTER
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